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M. P. Lin

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Sep 2026

Multi-Agent Artificial Intelligence Model to Enhance Self-Regulated Learning and Conceptual Understanding in Computer Science Education

This study explores the integration of a multi-agent AI system designed to support self-regulated learning (SRL) in computer science education. Building on preliminary work that introduced a Teaching Assistant AI (TA-AI) for real-time scaffolding, an Analytics-AI for pattern recognition, and an AI-Improver for iterativ...

Jing Huang, Seong Min Park, M. P. Lin et al. · 0 citations
Review Open access Jul 2026

Designing for Self-Regulated Learning in AI-Assisted Quizzing: A Classroom Pilot Study

A classroom-deployed quiz system that combines integrity-preserving hinting (TA-AI), trace summarization (Analytics-AI), and feedback-driven refinement (AI-Improver) to generate instructor diagnostics from routine interaction logs is presented.

M. P. Lin, Daniel H. Chang, V. Janarthanan et al. · 0 citations

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